Weather Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_alertsB | Get weather alerts for a US state. |
| get_forecastB | Get weather forecast for a location using coordinates. |
| get_forecast_by_cityB | Get weather forecast for a city by name. |
| get_current_conditionsB | Get current weather conditions for a location. |
| compare_weatherA | Compare current weather conditions between two locations. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Most tools have distinct purposes, but there is notable overlap between get_forecast and get_forecast_by_city, which both provide forecasts but use different input formats (coordinates vs. city name). This could cause confusion for an agent deciding which to use. The other tools (compare_weather, get_alerts, get_current_conditions) are clearly distinct.
The naming follows a consistent verb_noun pattern (e.g., get_forecast, get_alerts, get_current_conditions), with all tools using snake_case. The only minor deviation is compare_weather, which uses a verb_noun format but starts with 'compare' instead of 'get', which is reasonable given its distinct function.
With 5 tools, the count is well-scoped for a weather server, covering key functions like current conditions, forecasts, alerts, and comparisons. Each tool serves a clear purpose without being overly sparse or bloated, fitting typical expectations for such a domain.
The tool set covers core weather operations effectively, including current conditions, forecasts, alerts, and comparisons. A minor gap is the lack of historical weather data or more specialized features like air quality, but agents can work around this for most common use cases without significant failures.